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An abstract of the article "Site directed mutagenesis studies on HIV-1 reverse transcriptase (RT) shed light on the mechanism of action of a new Ribonuclease H/DNA polymerase RT dual inhibitor," by Angela Corona and colleagues is presented.

The phytochemical investigation of the methanol extract of the seeds of Magydaris pastinacea afforded two undescribed benzofuran glycosides, furomagydarins A-B ( 1 , 2 ), together with three known coumarins. The structures of the new isolates were elucidated after extensive 1D and 2D NMR experiments as well as HR MS. Compound 1 was able to inhibit the COX-2 expression in RAW264.7 macrophages exposed to lipopolysaccharide, a pro-inflammatory stimulus. RT-qPCR and luciferase reporter assays suggested that compound 1 reduces COX-2 expression at the transcriptional level. Further studies highlighted the capability of compound 1 to suppress the LPS-induced p38MAPK, JNK, and C/EBPβ phosphorylation, leading to COX-2 down-regulation in RAW264.7 macrophages.

Nine compounds, including two undescribed withanolides, withasomniferolides A and B (1 and 2), three known withanolides (3-5), a ferulic acid dimeric ester (6), and an inseparable mixture of three long alkyl chain ferulic acid esters (7-9), were isolated from a GABA A receptor positive activator methanol extract of the roots of Withania somnifera. The structures of the isolated compounds were elucidated based on NMR, MS, and ECD data analysis. In order to bioassay the single ferulic acid derivatives, compounds 6-9 were also synthesized. The most active compound, docosanyl ferulate (9), was able to enhance the GABA A receptor inhibitory postsynaptic currents with an IC 50 value of 7.9 μM. These results, by showing an ability to modulate the GABA A receptor function, cast fresh light on the biological activities of the secondary metabolites of W. somnifera roots.

Computational chemistry has always played a key role in anti-viral drug development. The challenges and the quickly rising public interest when a virus is becoming a threat has significantly influenced computational drug discovery. The most obvious example is anti-AIDS research, where HIV protease and reverse transcriptase have triggered enormous efforts in developing and improving computational methods. Methods applied to anti-viral research include (i) ligand-based approaches that rely on known active compounds to extrapolate biological activity, such as machine learning techniques or classical QSAR, (ii) structure-based methods that rely on an experimentally determined 3D structure of the targets, such as molecular docking or molecular dynamics, and (iii) universal approaches that can be applied in a structure- or ligand-based way, such as 3D QSAR or 3D pharmacophore elucidation. In this review we summarize these molecular modeling approaches as they were applied to fight anti-viral diseases and highlight their importance for anti-viral research. We discuss the role of computational chemistry in the development of small molecules as agents against HIV integrase, HIV-1 protease, HIV-1 reverse transcriptase, the influenza virus M2 channel protein, influenza virus neuraminidase, the SARS coronavirus main proteinase and spike protein, thymidine kinases of herpes viruses, hepatitis c virus proteins and other flaviviruses as well as human rhinovirus coat protein and proteases, and other picornaviridae. We highlight how computational approaches have helped in discovering anti-viral activities of natural products and give an overview on polypharmacology approaches that help to optimize drugs against several viruses or help to optimize the metabolic profile of and anti-viral drug.

Cannabinoid receptor 2 (CB(2) receptor) ligands are potential candidates for the therapy of chronic pain, inflammatory disorders, atherosclerosis, and osteoporosis. We describe the development of pharmacophore models for CB(2) receptor ligands, as well as a pharmacophore-based virtual screening workflow, which resulted in 14 hits for experimental follow-up. Seven compounds were identified with K(i) values below 25 microM. The CB(2) receptor-selective pyridine tetrahydrocannabinol analogue 8 (K(i) = 1.78 microM) was identified as a CB(2) partial agonist. Acetamides 12 (K(i) = 1.35 microM) and 18 (K(i) = 2.1 microM) represent new scaffolds for CB(2) receptor-selective antagonists and inverse agonists, respectively. Overall, our pharmacophore-based workflow yielded three novel scaffolds for the chemical development of CB(2) receptor ligands.